樣本矩 的英文怎麼說

中文拼音 [yàngběnjǔ]
樣本矩 英文
sample moment
  • 樣 : Ⅰ名詞1. （形狀） appearance; shape 2. （樣品） sample; model; pattern Ⅱ量詞（表示事物的種類） kind; type
  • 本 : i 名詞1 （草木的莖或根）stem or root of plants 2 （事物的根源）foundation; origin; basis 3 （本錢...
  • 矩 : 名詞1. （畫直角或正方形、矩形用的曲尺） carpenter's square; square2. （法度; 規則） rules; regulations 3. [物理學] moment
  • 樣本 : sample book; specimen; advanced copy; sample; muster; scantling; instance; statistics
  1. The signal we named it fundamental wave ; according to the fundamental wave, coefficients of the fundamental wave can be lined in a sequence. when the unique of the dissolve of the fundamental wave can be confirmed, the sequence of the coefficients can be regarded as one of representation forms of the signal itself ; theory of dissolvable signal shows that when order of the matrix of fundamental wave sampling equals to number of fundamental waves, the sequence of the sampling values from sampling points must be matched one by one with the sequence of the coefficients of fundamental waves. the sampling composed by sequences of the sampling values must be full sampling ; the relevant deductions of the theory of dissolvable signal shows that when sampling the signal, sampling frequency must be lager than the ratio of the number of fundamental waves to the occupation time of the fundamental waves ; to band - limited signals, when the fundamental wave is a sine signal, the results from the relevant deductions of theory of dissolvable signal is coherent to the classic sampling theory

    本文通過分析認為，當信號集中的任一信號可表示為一系列已知信號的線性代數和時，信號集便構成可分解信號集，已知信號稱為基波信號；對可分解信號而言，基波系數構成一序列，當對指定的基波信號集分解唯一確定時，系數序列本身便是信號的一個表示；可分解信號采樣定理指出當基波樣值矩陣的秩等於基波數時，則由采樣點處的采樣樣構成的樣值序列必與基波系數序列一一對應，從而由該樣值序列構成的采樣必為完全采樣；可分解信號采樣定理中的推論指出，對信號集進行采樣，采樣頻率必須大於其信號分解的基波數與其對應時長之比；對有限帶寬信號，若基波信號為正弦信號時，由可分解信號采樣定理推論給出的結論與經典采樣定理一致。
  2. For the given sample points, and matrix formed by covariance function with sample points as parameters, when the number of sample points approaches infinite, it is proven that this matrix spectrum will approach the spectral approach theorem for positive - definite kernel of integral equation

    對給定的樣本點，由樣本點為變量的協方差函數構成的矩陣，當樣本點個數趨于無窮大時，證明此矩陣譜逼近於積分方程正定核的譜逼近定理。
  3. Utilising dissolved gases analysis, a new insulation fault diagnosis method for power transformers is proposed. this method is based on the group grey relational grade analysis method. first, according to the fault type and grey reference sequence structure, some typical fault samples are divided into several sets of grey reference sequences. these sets are structured as one grey reference sequence group. secondly, according to a new calculation method of the grey relational coefficient, the individual relational coefficient and grade are computed. then according to the given calculation method for the group grey relation grade, the group grey relational grade is computed and the group grey relational grade matrix is structured. finally, according to the relational sequence, the insulation fault is identified for power transformers. the results of a large quantity of instant analyses show that the proposed method has higher diagnosis accuracy and reliability than the three - ratio method and the traditional grey relational method. it has good classified diagnosis ability and reliability

    基於變壓器油中溶解氣體分析，提出了一種基於群灰色關聯度分析的變壓器絕緣故障診斷新方法.首先根據故障類型與灰色參考序列構造，選擇變壓器典型故障樣本構造多組參考序列，這些參考序列組構成一個灰色參考序列群.其次根據給出的新的關聯系數計算方法，計算個體關聯系數和關聯度.然後根據給出的群灰色關聯度計算方法，計算群灰色關聯度和構造群灰色關聯度矩陣.最後根據關聯序識別變壓器絕緣故障診斷.通過大量變壓器絕緣故障診斷實例分析，所提方法診斷準確性與可靠性優於三比值法和傳統的灰色關聯分析方法，具有較好的分類診斷能力和可靠性
  4. In rsdm, binary patterns are replaced by real - valued patterns, accordingly avoiding the coding process ; the outer learning rule is replaced by regression rule, therefore the model has not only the ability of pattern recognition but the ability of function approximation. the prearrangement of the address array bases on the distribution of patterns. if the distribution of patterns is uniform. then the address array is prearranged randomly, otherwise predisposed with the theory of genetic algorithm and the pruneing measure so as to indicate the distribution of patterns and improve the network performance. non - linear function approximation, time - series prediction and handwritten numeral recognition show that the modified model is effective and feasible

    在rsdm中，以實值模式代替二值模式，避免了實值到二值的編碼過程：以回歸學習規則代替外積法，使該模型在具有識別能力的同時具有了對函數的逼近能力；地址矩陣的預置根據樣本的分佈採取不同方法，若樣本均勻分佈，則隨機預置，否則利用遺傳演算法的原理和消減措施來預置地址矩陣，使之反映樣本的分佈，改善網路的性能。
  5. It is especially attractive for the downlinks and suppressing intercell mai. when multiuser detector is adapted in blind mode, it usually adopts eignvalue decomposition or singularvalue decomposition of received sample correlation matrix and tracking alrithgms, which result in high computational complexity. at the same time, approximation computation in tracking alrithgms also result in slow convergence

    為實現盲自適應檢測，通常採用對接收信號樣本矩陣進行特徵值分解（ evd ）或奇異值分解（ svd ）后進行跟蹤，由此帶來的子空間秩跟蹤使得實現復雜度很高；另一方面，在跟蹤演算法中考慮一些實際情況而作出近似處理，從而引起誤差積累和正交性誤差，導致每次跟蹤開始階段跟蹤速度變慢。
  6. Hi the aspect of symmetry analyzing to the hopfield model neural network with hebbian learning, we study on the dynamical behavior of the state space under the action of isometric transformation group g = z2 ? n, and prove the invariant property of the energy orientation ? / / " ) of the state space under the action of g. we find that the symmetry relationship of the network is sx - sw = sh when the active function of the neuron is odd, where sx is the symmetry of the patterns set x under hebbian learning rule, sh is the symmetry of the network and sw is the symmetry of the weight matrix w of the network

    ） s _ n為手段，研究了網路狀態空間在群g作用下各點的運動情況，證明了群g作用下的不變性。證明了當神經元的激活函數f為奇函數時， hebb法則下存儲樣本集x的對稱性s _ x 、網路對稱性s _ h以及連接矩陣對稱性s _ w三者之間滿足s _ x = s _ w = s _ h的關系；同時，我們還證明了：網路穩定態集vf同一s _ h軌道中的兩個穩定態的動力學行為（能量和吸引域大小）相同；兩個等距網路h和h 1 = g ? h ， （ ? ） g （
  7. The kanerva ' s sparse distributed memory ( sdm ) tackles the problem of training large data patterns and extendes the storage mode of existing computer. but it ' s address array produced randomly ca n ' t reveal the distribution of patterns and it has ' t the ability of function approximation for its learning rule

    Kanerva的稀疏分佈存儲（ sdm ）模型解決了大維數樣本的訓練問題，推廣了現有計算機的存儲方式。但其地址矩陣的隨機預置方式不能反映樣本的分佈，並且sdm的學習方式使之不能用於函數逼近及時間序列預測問題。
  8. ( 2 ) a new method, which can be used to diagnose steam turbine generator - set ' s multiple faults, is brought out. this method, which is based on fuzzy clustering analyze theory, puts standard fault samples and the checked samples together as classified samples and draw a conclusion by using transfer closure based on fuzzy equivalence matrix

    （ 2 ）運用模糊聚類分析理論，將標準故障樣本和侍檢數據一起作為分類樣本，利用基於模糊等價矩陣的傳遞閉包法，提出了一種用於汽輪發電機組多故障診斷的新方法。
  9. We also prove the following properties : the stable states of the network in the same sh orbit have a same dynamical behavior, such as the size of attraction basin and the energy ; the relation of the symmetry of two isometric networks h and h ' = g - h is s ' h = g - sh - g ~ } for any isometry g, where sh and s ' h are the symmetry of h and h " respectively ; the isometry will not change the dynamical properties of the stable states set of the corresponding networks ; etc.

    ） g的對稱性s _ h和s _ n的關系為s _ h = g ? s _ h ? g ~ （ - 1 ） ；等距變換不會改變網路穩定態集的動力學性質等一系列的結論。所有這些研究結果表明了hebb學習法則是通過調整網路的連接矩陣，使得其的結構的對稱性包含存儲樣本集的對稱性這一存儲機理。
  10. It process documents not only based on latent semantic analysis, but also based on text multilevel dependency structure. the method first analysis the latent semantic structure of texts, make single value decomposition on text - matrix, reconstruct the semantic matrix ; then a method based on text multilevel dependency structure is adopted, deeply analysis the content of the semantic matrix, abstract the important sentences to generate abstraction and make up the shortage of latent semantic analysis on structure and syntax

    首先通過對文本進行潛在語義分析，對文本矩陣進行相應的奇異值分解，重構語義矩陣;然後採用基於篇章多級依存結構的文摘分析方法，對重構的語義矩陣表示的文本內容進行深入的分析，抽取重要的句子生成文摘，這樣就彌補了潛在語義分析在詞法和句法分析上的不足;同時過濾和去除了語義噪音，縮小了問題的規模。
  11. We found that the ergodic method used to calculate the symmetries of a multidimensional system would give rise to the computing complexity problem, hi order to avoid the computing complexity problem, we present a novel approach using genetic algorithms for calculating the permutation symmetries of a patterns set and the weight matrix of the network. we design the corresponding computer program with visual c + + 6. 0 language. and numerical simulat

    並用wsualc語言分別設計了求解網路連接矩陣和給定樣本集的置換對稱性相應的遍歷法和遺傳演算法的程序，在pc機上進行數值模擬計算，比較遍歷法和遺傳演算法的計算結果。
  12. Under ideal conditions, adaptive array signal processing methods can get excellent performance and adaptive beamformers provide an improvement in array output signal - to - interference - plus - noise - ratio ( sinr ) in comparison with conventional beamforming. in practical operating circumstances, the performance of adaptive array signal processing methods degrade extremely due to existing errors

    但是，在實際系統中總存在有誤差，包括自適應訓練樣本有限次快拍引起的協方差矩陣的估計誤差和各種系統誤差，誤差使得實際陣列流形與理想陣列流形存在差異，這時自適應陣列信號處理的性能會急劇下降。
  13. In this paper, we present the sufficient and necessary condition for the sum of a identity matrix and a generalized cyclic matrix is nonsingular, and obtain the formal representation of the relative gain array of the sum matrix

    本文給出了單位矩陣與廣義循環矩陣的和矩陣的非奇異的充要條件，得到了這樣和矩陣的相對增益陣列的顯示表達式。
  14. ( 5 ) a series of design methods of classifiers are proposed, including the classifier based on the generalized inverse and the probabilistic reasoning method ( prm ), a new self - adaptive kohonen clustering network which overcomes the shortcomings of the conventional clustering algorithms, and the fuzzy neural classifier. the experimental study efface recognition is presented based on the combination of multi - feature multi - classifier. ( 6 ) this paper proposes a hybrid feature extraction method for face recognition, which is a combination of the eigen matrix, fisher discriminant analysis, and the generalized optimal set of discriminant vectors

    （ 5 ）對圖象分類器設計方法進行研究，主要包括：提出了一種基於廣義逆和概率推理的分類器設計方法；提出了一種新的自適應模糊聚類演算法；提出了基於模糊神經網路的分類器設計方法；並對多特徵多分類器組合方法在人臉識別中進行實驗研究； （ 6 ）提出了一種只要一個訓練樣本就能解決人臉識別問題的新方法，該方法結合了特徵矩陣、 fisher最優鑒別分析和廣義最優鑒別分析方法的優點。
  15. In this thesis, we adopt the technique of statistical training, create a sample database of every kinds of expression face images, construct a matrix of the difference of each sample and average image, and reduce dimension by pca, then decrease the relativity of principle components by ica, and therefore get the character sub - space of face. when detecting a face, we adopt the method of disturbing principle components of model to match special facial image, which is called whole optimization method in this thesis

    論文採用統計訓練的思想，選擇包括各種表情變化的人臉圖像建立樣本庫，取所有樣本與平均圖像的差構造一個矩陣，利用主元分析方法進行降維，然後通過獨立元分析降低主元相關性，建立了人臉的特徵子空間；演算法採取對主元進行擾動優化匹配的方法檢測人臉，本文稱此方法為全局最優的方法。
  16. A novel fault diagnostic strategy based on time - varying dynamic pca model has been presented, which makes use of continuous updating time - lagged data matrix to construct a changeable pca model to fulfill the task of fault detection and identification

    摘要提出利用不斷更新的時滯數據矩陣建立變化的動態主元模型對某些動態系統內的傳感器故障進行檢測，利用變量貢獻圖的樣本平均對故障進行識別的方法。
  17. The first order conditions are also the sample counterparts of the related population moments

    一階條件也是相關的總體矩在樣本中的對應。
  18. 2. according to distribution characteristic of recipes, a recipe fuzzy cluster algorithm based on kernel - function was presented. firstly one recipe kernel - function was defined to represent recipe class, through minimizing all the distance of recipe samples to recipe class kernel, recipe samples were classed. the class number was gave out and each recipe was gave membership degrees belong to each classes

    2 、根據配方的模式分佈特點，提出了一種基於類核函數的配方模糊聚類演算法，定義一個配方類核函數來代表配方類，通過最小化所有配方樣本到配方類核距離加權和來對配方進行聚類，得到聚類數目及模糊隸屬度矩陣。
  19. According to the requirements to pd pattern auto - recognition, this paper studies systematically the basic theories and realizable methods for auto - recognition of pd gray intensity image : ( 1 ) in the requirement of on - line pd monitoring for transformer, several discharge models are designed and the relevant experiment methods projected. with discharge model tests, a lot of discharge sample data is acquired. on the base of systematical research on recognition for pd gray intensity image, this paper puts forward two kinds of fractal features, the 2nd generalized dimensions of original pd images and fractal dimensions of high gray intensity pd images, and then the relevant extraction methods

    針對局部放電模式自動識別的需要，作者系統地研究了局部放電灰度圖像自動識別中的基本理論和實現方法： （ 1 ）根據變壓器局部放電在線監測的要求，設計了放電模型和實驗方法，並通過模型實驗獲得了大量放電樣本數據，為構造局部放電灰度圖像和採用bpnn進行識別作好準備； （ 2 ）研究了局部放電灰度圖像的構造方法以及降維構造32 32灰度和矩陣的方法；在用人工神經網路對局部放電進行模式識別時，分析了bp網路的優缺點，對典型bp網路的結構和學習訓練演算法提出了改進，採用帶有偏差單元的遞歸神經網路作為模式分類器；採用32 32灰度和矩陣進行bpnn識別結果表明這種方法是有效的。
  20. Sample correlation matrix

    樣本相關矩陣
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